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Review of Fundamental Proof Methods in Computer Science: a Computer-Based Approach

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Review of Fundamental Proof Methods in Computer Science: a Computer-Based Approach Review of Fundamental Proof Methods in Computer Science: A Computer-Based Approach Selmer Bringsjord • Naveen Sundar G. • Atriya Sen January 17, 2020 1 Introduction Fundamental Proof Methods in Computer Science: A Computer-Based Approach (= FPMICS) by Arkoudas and Musser (= A&M) is a positively marvelous book, one symbiotically united with the longstanding Athena environment, by our lights the best mechanical proof assistant available at this time, especially when proof pedagogy is a requirement for such an assistant.1 FPMICS is also, by any metric, lengthy: 941 pages, tip to toe. Nonetheless, in our opinion, for those determined to teach or learn how to produce substantive proofs in the 21st century and beyond, FPMICS is peerless, and gradually digesting it, with Athena at one’s side along the way, will produce in the learner a deep understanding of proof in the context of both computer science and artificial intelligence (AI). Such deep understanding is central to at least the following areas in computer science: software verification, theory of computation, algorithms, programming languages; and the following in AI: automated reasoning (specifically automated deduction), and logic-based AI.2 We are of the opinion that using the FPMICS-Athena pair is also ideal for teaching and learning the art of proof in cognate fields, e.g. extensional logic (as we point out below, FPMICS provides no coverage of intensional logic, e.g. modal logic) as traditionally taught in mathematics and philosophy. It is important for potential readers of FPMICS to understand that this book arises from an affirmation of suitably high standards for what makes for a knowably valid proof. These standards are very nicely conveyed by a deceptively simple example that launches the book in earnest — an example of an informal proof that happens to be, after refinement, ultimately valid, but in its initial form is certainly not verifiably valid: no machine proof checker, nor for that matter no sufficiently careful human checker, would accept the informal proof in question. In the example, what is to be proved is the algebraic identity (let’s label it ‘τ’) (a−1)−1 = a from the set I of these three axioms: • Right-Identity: x · I = x • Left-Identity: I · x = x • Right-Inverse: x · x−1 = x The informal proof is a chaining sequence shown in Figure 1. Is this a formally valid proof? That is, is each step correct on the basis of what we are supplied as starting material? More precisely and using customary notation in formal logic, computer science, AI, and formal philosophy, is it 1Athena, and the novel formalisms that undergird it, also powers a paradigm for programming and computation, for formal-methods scientists and professional practitioners (e.g. see Arkoudas 2001). While we as a matter of fact find this paradigm attractive, it is outside the scope of the present review. We also regard it to be outside the review to defend our opinion that Athena, in no small part because of its deep linkage to natural deduction (which by definition is in accord with how humans in the business of proving things go about doing so), is the best mechanical proof assistant available to not just students, but professionals in automated reasoning. 2A presentation of logic-based AI, a form of AI for which FPMICS-Athena is a perfect match, is given e.g. in (Bringsjord 2008). In the opinion of the first author of the present review, computer science itself should be identified with abstract formal logic and automated reasoning (for a defense see (Bringsjord forthcoming)); and if this position is affirmed (even to just an appreciable degree), FPMICS-Athena might well then be the vehicles to use when introducing computer science itself to students. 1 (a−1)−1 = I · (a−1)−1 = (a · a−1) · (a−1)−1 = a · (a−1 · (a−1)−1) = a · I = a Figure 1: Simple, Informal, Ultimately Formally @@latex:In@@valid Chaining Proof true that I ` τ? No. To many, if not most, this will seem to be perfectly valid proof, but it is not. This will be revealed by any attempt to mechanically verify the proof, for such an attempt, as A&M point out, will among other things reveal that the reasoning is enthymematic, since e.g. associativity is absent from I but very much needed for the third step in the informal proof. The complete analysis and refinement of this informal proof by A&M points succinctly forward to much of what FPMICS covers. 2 Brutal Encapsulation of FIPMICS As to what FPMICS covers, here’s an encapsulation, inevitably rather brutal given the length of the book. As we’ve already noted, A&M immediately draw the reader in with the equality-chaining ex- ample referred to above; and with the analysis of that specimen completed and the entire road ahead inspired, then provide in Chapter 2 a self-contained, lucid introduction to Athena — one suitable not only for students, but professionals intending to explore subsequent, advanced use of this cutting-edge proof assistant. Part II of the book now commences, and consists, first, in a re- turn to equality chaining, replete with coverage of more advanced techniques, including automated conjecture testing. A&M then move within Part II to a remarkably efficient and innovative proof- oriented coverage of zero-order logic (= L0) in Chapter 4, including a hands-on summary of SAT solving (a still-vibrant area of AI and automated reasoning today), and a final section in which is given an elegant implementation of a method that takes an L0 sentence φ to a proof if φ is a theorem, and fails otherwise. Chapter 5, an absolutely key part of the FPMICS-Athena pair, covers L1 (= first-order logic) masterfully, and its penultimate section, “Additional exercises,” ends with an exercise that, pedagogically, we find to be a perfect gauge as to whether the student of proof methods is really and truly ready to move forward from this point to more challenging material, in which robust formal proofs, and what it takes to obtain them, are obtained. This exercise (a clever one from Suppes 1951) is given at almost exactly the half-way point of the book, and consists in the challenge of proving eight theorems about the logic of a naïve scale used to measure the relative mass of two objects x and y. Chapter 5 ends with “5.8 Chapter notes,” a rather unassuming, less- than-two-page section that we nonetheless regard to crucial to an understanding of A-M, because there the authors explicitly affirm the centrality of relatively inexpressive many-sorted L1 to their paradigm, and the basic rationale of their having explicitly and unabashedly placed this logic in this special position, to the exclusion e.g. of category theory and higher-order logic/type theory. (We return to the the issue of expressivity momentarily.) The last chapter in Part II, 6, extends and refines the chaining style of proof, which is then followed for the remainder of the volume. Part III of FPMICS, comprising Chapters 7–10, is devoted to proofs involving key discrete 2 structures, including natural numbers, integers, sets (finite only, sensibly), and maps; the latter, a standard abstract data type, will be known to some of our readers as dictionaries or associative arrays. Part IV of the book, composed of two chapters (17, in which is elegantly given a correct proof for a humble compiler; and 18, which revolves around While, a simplified imperative programming language), is devoted to representing and deductively reasoning about programming languages, and for those hoping the FPMICS-Athena combination will to provide a portal to software verification, this Part will not disappoint. FPMICS ends with two appendices, the first (A) a streamlined account of the syntax and semantics of Athena’s core constructs, and the second (B) a remarkably economical but informative presentation of logic programming and Prolog (which includes the best intuitive but accurate encapsulation of least Herbrand models we have seen). Appendix B ends with coverage of an Athena implementation of a Prolog interpreter for definite clauses. 3 Expressivity and the A-M Paradigm Returning as promised to the question of expressivity, extensional formal logics, as is well-known, are routinely cast in a continuum, with their location in this continuum determined by how expressive they are. For instance, L0 has no trouble expressing the sentence “Six is greater than five” (e.g. G(6¯; 5)¯ , where use of the bar simply indicates that the symbol beneath it is one stipulated in the formal language to denote some entity outside this language), but cannot express this sentence: “There are at least two numbers greater than 5.” For this we need quantifiers, and they are not available in L0. They are available, however, in L1; for in this logic we can capture the English sentence in question with for instance this formula: φ := 9n9m[n 6= m ^ G(n; 5)¯ ^ G(m; 5)]¯ ; which of course makes use of L1’s existential quantifier to get the job done. As we have conveyed above, FPMICS in general, and Athena in particular, offers all that’s needed to represent and deductively reason over formulae like φ. But consider the following sentence, which even very young students can see is true (w.r.t. the natural numbers): “There are at least two numbers greater than five, and they share at least one property with the number zero.” This sentence can’t be expressed in L1; but it can be easily captured in L2, second-order logic, like this: := 9n9m[n 6= m ^ G(n; 5)¯ ^ G(m; 5)¯ ^ 9X(X(n) ^ X(m) ^ X(0))] Unfortunately, is beyond the reach of FPMICS-Athena, and we do find this objectionable.
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